Version control. We version everything.

Unlike traditional version control systems, dotscience can version arbitrarily large datasets.

It uses a copy-on-write file system that allows it to take ‘thin’ snapshots as the data changes, for instance as you clean it, add to it, and perform feature engineering.

If your data isn’t stored in a local directory, for instance if its accessed using S3, GCS or Azure blob storage or via Apache Spark, we can version that too by taking a secure snapshot as the data is read.

When if you try to pull the data again, Dotscience will notify you if it has changed from the stored snapshot.

Beta experiment tracker

Dotscience captures and versions.

Model code

Parameters and hyperparameters

Keep your model immutably linked with its training data.

Dotscience runs your script in a Docker container, wherever you choose to run it. This lets us record all information about the model’s runtime environment.

Such as a serialised model, output files and logs.

Metrics about model fitting, such as F score or RMSE, or about runtime.

Sign up for our beta

Our beta testers get early access to dotscience for free. Not only can you help shape the product, you can start using it right now in your workflows.